CS360 Machine Learning Final Project - Vincent Yu

Using Time Series ML Models for COVID Data Analysis and Predictions

---

0. Imports

Before getting started, import the necessary packages and helper functions.

import os

import numpy as np
import pandas as pd

# For interactive graphs
import plotly.express as px
import plotly.graph_objects as go

# Local imports
from utils import *

1. Project Introduction

2. Data

dst = os.getcwd() + '/data/CONVENIENT_us_confirmed_cases.csv' 
dset = read_dataset(dst)
dates = dset['dates']
fig = go.Figure()
for state in dset.keys():
    if state != 'dates':
        fig.add_trace(go.Scatter(x=dates, y=dset[state],
                    mode='lines+markers',
                    name=state,
                    visible = "legendonly"))

fig.show()

dst = os.getcwd() + '/data/CONVENIENT_us_deaths.csv' 
dset = read_dataset(dst)
dates = dset['dates']
fig = go.Figure()
for state in dset.keys():
    if state != 'dates':
        fig.add_trace(go.Scatter(x=dates, y=dset[state],
                    mode='lines+markers',
                    name=state,
                    visible = "legendonly"))

fig.show()

3. Models

The models selected are...

4. Conclusions and Future Work

Last Updated: 11/28/2020